1. 1 Terrain-Constrained Mobile Sensor Networks Shu Zhou 1, Wei Shu 1, Min-You Wu 2 1.The University of New Mexico 2.Shanghai Jiao Tong University IEEE Globecom 2005

2. 2 Outline Introduction Introduction System Framework System Framework Detection improvement Detection improvement Cost and Risk Cost and Risk Path Planning Path Planning Matching Matching Simulation Simulation Conclusion Conclusion

3. 3 Introduction --- Background Monitoring area

4. 4 Introduction --- Problem statement The effects of terrain have to be considered Types of terrain The loss ratio of mobile sensors Consume different amount of energy Elevation Consume different amount of energy

5. 5 Introduction --- Problem statement Sensing ability of s i at position a as s(i, a) Overall detection probability at position a Sensor field A, the overall detection probability

6. 6 Introduction --- Motivation and Goals Motivation Motivation Find the best destinations and the best paths for mobile sensors Find the best destinations and the best paths for mobile sensors Goals Goals Maximize the detection probability of the sensor filed Minimize the power consumption and loss ratio of mobile sensors

7. 7 System Framework --- Assumptions Sensor networks are randomly deployed Sensor networks are randomly deployed Holes and weak areas of detection are inevitable Holes and weak areas of detection are inevitable

8. 8 System Framework --- Overview Before mobile sensors move After mobile sensors move

9. 9 System Framework --- Detection improvement When a sensor is placed at some position a The overall improvement

10. 10 System Framework --- Cost and Risk Preprocess the map to compress type and elevation information Original Terrain Terrain Type Terrain Elevation

11. 11 System Framework --- Cost and Risk Cost of moving: F:The force of s i ’ s engine: θ

12. 12 System Framework --- Cost and Risk Risk Risk of moving Elevation-based: Elevation-based: Type-based: Type-based:

13. 13 System Framework --- Path Planning Use modified RRT-connect Algorithm Use modified RRT-connect Algorithm Find the optimal path from a mobile sensor ’ s original location to its destination Find the optimal path from a mobile sensor ’ s original location to its destination

14. 14 System Framework --- Matching Each mobile sensor select destination candidates Within the maximum possible range Within the maximum possible range The path is a straight line in plan dirt road The path is a straight line in plan dirt road Positions that have big detection probability improvement Positions that have big detection probability improvement

15. 15 System Framework --- Matching Stable marriage algorithm to match mobile sensors with all the destination candidates Mobile sensors want to move the same destination candidate Mobile sensors want to move the same destination candidate s1s1 s3s3 d1d1 d2d2 d3d3 s2s2

16. 16 System Framework --- Matching s1s1 s2s2 s3s3 d1d1 d1d1 d3d3 d2d2 d3d3 d2d2 d3d3 d2d2 d1d1 d1d1 d2d2 d3d3 s1s1 s1s1 s3s3 s2s2 s3s3 s2s2 s3s3 s2s2 s1s1 s 1 → d 1 1 s 2 → d 1 → d 3 → d 2 2 3 s 3 → d 3 4 5 (s 1, d 1 ) (s 2, d 2 ) (s 3, d 3 ) Not necessarily an optimal solution Sort by ratio: I(a)(1-R(b,a))/C(b,a) Sort by ratio: I(a)(1-R(b,a))/C(b,a)

17. 17 Simulation Sensor field: 1km 2 ground Sensor field: 1km 2 ground Sensing range: 20m Sensing range: 20m Randomly deploy 1000 stationary sensors Randomly deploy 1000 stationary sensors The weight of a mobile sensor: 200g The weight of a mobile sensor: 200g The total power of a mobile sensor: 5000J The total power of a mobile sensor: 5000J

18. 18 Simulation

19. 19 Simulation The average risk, cost and (1-R)/C of 150 mobile sensors The average risk, cost and (1-R)/C of 150 mobile sensors

20. 20 Conclusion Propose a terrain-aware framework of mobile sensor networks Study the behavior of the MSN under the constraints of terrain Present algorithms to get the best detection improvement